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UmbrellaDeleteComputer

API workflow to delete set number of roaming computers provided through a CSV File. This script has been tested with Umbrella v1 Management APIs and requires Python 3 running on the end machine.

Umbrella Management API does not provide BULK option by default and also has a rate limit in place as following.

  • 5 requests per second
  • 14 requests per minute
  • 350 requests per 30 minutes

When a rate limit is reached, the API returns the Too Many Requests error with the HTTP response code 429, for the remainder of the time-period. The script has been written to not hit this rate limit as we are using a timer of 6 seconds per API requests.

For more details about Management API : https://docs.umbrella.com/umbrella-api/docs/management-api-documentation

Installation

Installing the script is pretty straight forward . You can just copy and paste them into you python environment but a good practice is to run them into a python virtual environment.

Install a Python virtual environment

For Linux/Mac 

python3 -m venv venv
source bin activate

For Windows 

We assume that you already have installed git-bash.  If so open a git-bash console and :

python -m venv venv
source /venv/Scripts/activate

git clone the scripts

git clone https://github.com/shubhambharti89/UmbrellaBulkDeleteComputer.git
cd UmbrellaBulkDeleteComputer/

install needed python modules

These scripts use the following python modules

  • requests
  • json
  • csv
  • time

You can install these modules with the following :

pip install -r requirements.txt

Running the scripts

First you need to make couple of changes that needs to be done on the script main.py before using it. Provide the following two details to the script :

  • Organization ID
  • Management API Key

Code Changes

This workflow requires CSV File as an input - Sample CSV file is provided in this repository itself. Fill the CSV file with required roaming computer names and run main.py script present in respective folder.

Input CSV

Input Parmeters

Once the required details are provided, the output is seen as below(This is just an example):

Terminal Output

This script also provides you with a log file in the same folder with success and failure responses. The sample Success and Error logs are provided in the same repository

  • ErrorLog.txt
  • SuccessLog.txt
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